Public Member Functions | Protected Attributes | List of all members
WeightedAverageMethod Class Reference
Inheritance diagram for WeightedAverageMethod:
Inheritance graph
[legend]
Collaboration diagram for WeightedAverageMethod:
Collaboration graph
[legend]

Public Member Functions

 WeightedAverageMethod (const WeightedAverageMethod &method)
 
virtual void updateBean () const
 Called after setParameters()
 
virtual void add (AccumulationArray &accArray, const size_t i, double value, double weight) const
 Adds a weighted value to the accumulation array. More...
 
virtual void add (AccumulationArray &accArray, const size_t i, double value, double weight, unsigned int count) const
 Adds 'count' copies of a weighted value to the accumulation array. More...
 
virtual void extractValue (const AccumulationArray &accArray, const AccumulationConverter &coder, Image &dst, const drain::Rectangle< int > &crop={0, 0, 0, 0}) const
 Retrieve the accumulated values from the accumulation matrix back to a data array. More...
 
virtual void extractWeight (const AccumulationArray &accArray, const AccumulationConverter &coder, Image &dst, const drain::Rectangle< int > &crop={0, 0, 0, 0}) const
 Retrieves the (average) weight of the accumulated values. More...
 
virtual void extractDev (const AccumulationArray &accArray, const AccumulationConverter &coder, Image &dst, const drain::Rectangle< int > &crop={0, 0, 0, 0}) const
 Retrieves the standard deviation of the accumulated values. More...
 
- Public Member Functions inherited from AccumulationMethod
 AccumulationMethod (const AccumulationMethod &method)
 
virtual void extractCount (const AccumulationArray &accArray, const AccumulationConverter &coder, Image &dst, const drain::Rectangle< int > &crop={0, 0, 0, 0}) const
 Retrieves the count of values accumulated. More...
 
- Public Member Functions inherited from BeanLike
virtual const std::string & getName () const
 Return the name of an instance.
 
virtual const std::string & getDescription () const
 Return a brief description.
 
bool hasParameters () const
 
template<class F >
getParameter (const std::string &p) const
 Gets a single parameter.
 
const ReferenceMapgetParameters () const
 
ReferenceMapgetParameters ()
 
template<class F >
void setParametersFromEntries (const F &args)
 
void setParameters (std::initializer_list< Variable::init_pair_t > args)
 Grants access to (if above hidden)
 
virtual void setParameters (const std::string &p, char assignmentSymbol='=', char separatorSymbol=0)
 Sets comma-separated parameters in a predetermined order "a,b,c" or by specifing them "b=2". More...
 
template<class T >
void setParameters (const std::map< std::string, T > &args)
 Set parameters.
 
template<class T >
void setParameters (const SmartMap< T > &args)
 Set parameters.
 
void setParameter (const std::string &p, const Castable &value)
 Sets a single parameter.
 
template<class T >
void setParameter (const std::string &p, const VariableT< T > &value)
 
template<class F >
void setParameter (const std::string &p, const F &value)
 Sets a single parameter. More...
 
template<class F >
void setParameter (const std::string &p, std::initializer_list< F > value)
 Sets a single parameter.
 
BeanLikeoperator= (const BeanLike &b)
 
virtual std::ostream & toStream (std::ostream &ostr, bool compact=true) const
 
 BeanLike (const BeanLike &b)
 
 BeanLike (const std::string &name, const std::string &description="")
 

Protected Attributes

double bias = 0.0
 
double p = 1.0
 Power for data values.
 
double pInv = 1.0
 
bool USE_P = false
 
double r = 1.0
 Power for weights.
 
double rInv = 1.0
 
bool USE_R = false
 
- Protected Attributes inherited from BeanLike
const std::string name
 
const std::string description
 
ReferenceMap parameters
 

Additional Inherited Members

- Protected Member Functions inherited from AccumulationMethod
void initDstOLD (const AccumulationArray &accArray, const AccumulationConverter &coder, Image &dst, const drain::Rectangle< int > &crop) const
 Sets variables that depend on public parameters. Called by setParameters().
 
 AccumulationMethod (const std::string &name)
 
- Protected Member Functions inherited from BeanLike
virtual void storeLastArguments (const std::string &p)
 Called after setParameters()
 

Member Function Documentation

◆ add() [1/2]

void add ( AccumulationArray accArray,
const size_t  i,
double  value,
double  weight 
) const
virtual

Adds a weighted value to the accumulation array.

i - precomputed address in the array
value - value to be added
weight - weight of the value

Notice that not all the rules apply the weights. Semantically, the weights should reflect the importance, confidence or relevance of the value.

else (r==0, weight==0) just ++count, see above.

Reimplemented from AccumulationMethod.

◆ add() [2/2]

void add ( AccumulationArray accArray,
const size_t  i,
double  value,
double  weight,
unsigned int  count 
) const
inlinevirtual

Adds 'count' copies of a weighted value to the accumulation array.

else (r==0, weight==0), and just ++count, see above.

Reimplemented from AccumulationMethod.

◆ extractDev()

void extractDev ( const AccumulationArray accArray,
const AccumulationConverter coder,
Image dst,
const drain::Rectangle< int > &  crop = {0,0,0,0} 
) const
virtual

Retrieves the standard deviation of the accumulated values.

dst - target array in which the values are stored.
gain - scaling coefficient applied to each retrived value
offset - additive coefficient applied to each retrieved value
NODATA - if bin count is undetectValue that is, there is no data in a bin, this value is applied.

Reimplemented from AccumulationMethod.

◆ extractValue()

void extractValue ( const AccumulationArray accArray,
const AccumulationConverter coder,
Image dst,
const drain::Rectangle< int > &  crop = {0,0,0,0} 
) const
virtual

Retrieve the accumulated values from the accumulation matrix back to a data array.

In this context, the "value" refers to the main object of interest (measurement, prediction etc).

dst - target array in which the values are stored.
gain - scaling coefficient applied to each retrived value
offset - additive coefficient applied to each retrieved value
NEGLIBLE - if value is less than minValue (or weight is undetectValue but bin count non-undetectValue), this value is applied.
NODATA - if bin count is undetectValue that is, there is no data in a bin, this value is applied.

Reimplemented from AccumulationMethod.

◆ extractWeight()

void extractWeight ( const AccumulationArray accArray,
const AccumulationConverter coder,
Image dst,
const drain::Rectangle< int > &  crop = {0,0,0,0} 
) const
virtual

Retrieves the (average) weight of the accumulated values.

Parameters
accArray- data source
coder- logic for scaling and encoding the result \pararm dst - target array in which the data are stored.

Reimplemented from AccumulationMethod.


The documentation for this class was generated from the following files: